Statistical Mechanics of Time Domain Ensemble Learning

Conventional ensemble learning combines students in the space domain. On the other hand, in this paper we combine students in the time domain and call it time domain ensemble learning. In this paper, we analyze the generalization performance of time domain ensemble learning in the framework of online learning using a statistical mechanical method. We treat a model in which both the teacher and the student are linear perceptrons with noises. Time domain ensemble learning is twice as effective as conventional space domain ensemble learning.Comment: 10 pages, 10 figure

Algal polyunsaturated fatty acids and effects on plankton ecology and other organisms

A review and discussion of the effects of algal polyunsaturated fatty acids (PUFAs) on phytoplankton and zooplankton ecology and their effects on other animal systems. Topics discussed also include the relationship of cyanobacterial classification to PUFA occurrence, lipid concentrations occurring in the aqueous environment, the general effect of microalgae on zooplankton, and how algal PUFAs may be exerting their inhibitory and toxic effects

On-line Learning of an Unlearnable True Teacher through Mobile Ensemble Teachers

On-line learning of a hierarchical learning model is studied by a method from statistical mechanics. In our model a student of a simple perceptron learns from not a true teacher directly, but ensemble teachers who learn from the true teacher with a perceptron learning rule. Since the true teacher and the ensemble teachers are expressed as non-monotonic perceptron and simple ones, respectively, the ensemble teachers go around the unlearnable true teacher with the distance between them fixed in an asymptotic steady state. The generalization performance of the student is shown to exceed that of the ensemble teachers in a transient state, as was shown in similar ensemble-teachers models. Further, it is found that moving the ensemble teachers even in the steady state, in contrast to the fixed ensemble teachers, is efficient for the performance of the student.Comment: 18 pages, 8 figure

Statistical Mechanics of Nonlinear On-line Learning for Ensemble Teachers

We analyze the generalization performance of a student in a model composed of nonlinear perceptrons: a true teacher, ensemble teachers, and the student. We calculate the generalization error of the student analytically or numerically using statistical mechanics in the framework of on-line learning. We treat two well-known learning rules: Hebbian learning and perceptron learning. As a result, it is proven that the nonlinear model shows qualitatively different behaviors from the linear model. Moreover, it is clarified that Hebbian learning and perceptron learning show qualitatively different behaviors from each other. In Hebbian learning, we can analytically obtain the solutions. In this case, the generalization error monotonically decreases. The steady value of the generalization error is independent of the learning rate. The larger the number of teachers is and the more variety the ensemble teachers have, the smaller the generalization error is. In perceptron learning, we have to numerically obtain the solutions. In this case, the dynamical behaviors of the generalization error are non-monotonic. The smaller the learning rate is, the larger the number of teachers is; and the more variety the ensemble teachers have, the smaller the minimum value of the generalization error is.Comment: 13 pages, 9 figure

Adhesion, friction and micromechanical properties of ceramics

The adhesion, friction, and micromechanical properties of ceramics, both in monolithic and coating form, are reviewed. Ceramics are examined in contact with themselves, other harder materials, and metals. For the simplicity of discussion, the tribological properties of concern in the processes are separated into two parts. The first part discusses the pull-off force (adhesion) and the shear force required to break the interfacial junctions between contacting surfaces. The role of chemical bonding in adhesion and friction, and the effects of surface contaminant films and temperature on tribological response with respect to adhesion and friction are discussed. The second part deals with abrasion of ceramics. Elastic, plastic, and fracture behavior of ceramics in solid state contact is discussed. The scratch technique of determining the critical load needed to fracture interfacial adhesive bonds of ceramic deposited on substrates is also addressed

Statistical Mechanics of Linear and Nonlinear Time-Domain Ensemble Learning

Conventional ensemble learning combines students in the space domain. In this paper, however, we combine students in the time domain and call it time-domain ensemble learning. We analyze, compare, and discuss the generalization performances regarding time-domain ensemble learning of both a linear model and a nonlinear model. Analyzing in the framework of online learning using a statistical mechanical method, we show the qualitatively different behaviors between the two models. In a linear model, the dynamical behaviors of the generalization error are monotonic. We analytically show that time-domain ensemble learning is twice as effective as conventional ensemble learning. Furthermore, the generalization error of a nonlinear model features nonmonotonic dynamical behaviors when the learning rate is small. We numerically show that the generalization performance can be improved remarkably by using this phenomenon and the divergence of students in the time domain.Comment: 11 pages, 7 figure

Policy problems relating to the labor immigration control in Japan

This paper provides analyses of the following issues: i) The desirable Japanese admittance system of foreign workers, ii) The effects on the Japanese population structure and economy to which immigrants may have. The analyses insist that Japan should introduce the point system to examine the admittance of foreign workers, and grant permanent residence to them at the time of new entry, but the benefit from admitting immigrants would be small and diminish according to aging of the immigrants group.